Image-Text-to-Text
MLX
Core ML
apple
ocr
document-parsing
multi-page
deepseek-ocr
Mixture of Experts
fluidinference
Instructions to use FluidInference/unlimited-ocr-mlx-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use FluidInference/unlimited-ocr-mlx-coreml with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("FluidInference/unlimited-ocr-mlx-coreml") config = load_config("FluidInference/unlimited-ocr-mlx-coreml") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download UnlimitedOcrDecoder.mlpackage/Data/com.apple.CoreML/model.mlmodel from FluidInference/unlimited-ocr-mlx-coreml: direct link, hf CLI and curl.
- Browser
- Download file 3.42 MB
-
https://huggingface.co/FluidInference/unlimited-ocr-mlx-coreml/resolve/main/UnlimitedOcrDecoder.mlpackage/Data/com.apple.CoreML/model.mlmodel
- Command line
-
hf download hf://FluidInference/unlimited-ocr-mlx-coreml/UnlimitedOcrDecoder.mlpackage/Data/com.apple.CoreML/model.mlmodel
-
curl -L -o model.mlmodel https://huggingface.co/FluidInference/unlimited-ocr-mlx-coreml/resolve/main/UnlimitedOcrDecoder.mlpackage/Data/com.apple.CoreML/model.mlmodel
3.42 MB
- Xet hash:
- fe07c36b57136895dd298e4c87cec332b22981bec2522f4745af37da24afb37a
- Size of remote file:
- 3.42 MB
- SHA256:
- 4a339171fbfd8ca84a1de4d39de77d53538feb7e4bb9759d3fb92b3d0ee20ee2
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